code: def get_mean_and_var(self, axis, gamma, x, xp, interm_dtype):
      tmp = xp.empty(gamma.size * 2, dtype=gamma.dtype)
      x.mean(axis=axis, out=tmp[: gamma.size], dtype=gamma.dtype)
      xp.square(x).mean(
          axis=axis, out=tmp[gamma.size :], dtype=gamma.dtype
      )
      if xp is cuda.cupy:
          chainer.cuda.Stream.null.synchronize()
      self.comm._multi_node_mean(None, tmp)
      mean = tmp[: gamma.size]
      sqmean = tmp[gamma.size :]
      var = sqmean - xp.square(mean)
      return mean, var
  
file_path: chainer/chainermn/functions/batch_normalization.py
imports: import chainer
  from chainer.backends import cuda
  from chainer.functions.normalization import batch_normalization
  import chainer.utils
label_desc: Use image node_id 2 for calling the _MpiImpl obj's underlying member method code with example usage: obj.get_mean_and_var(axis, gamma, x, xp, interm_dtype) and returns: mean,  var